D465 Data Applications

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Free D465 Data Applications Questions

1.

An analyst uses interactive documents to perform analyses that are compatible with R, are an alternative to R Markdown, and can be used for anything from data cleaning and transformation to statistical modeling and visualizations. What should the analyst use?

  • Published visualization
  • Jupyter notebook
  • HTML presentation
  • GitHub document

Explanation

Explanation

Correct answer: (B.) Jupyter notebook
A Jupyter notebook is an interactive computing environment that supports multiple programming languages, including R through kernel integration. It allows analysts to combine executable code, visualizations, and narrative text in a single document, making it suitable for tasks such as data cleaning, transformation, statistical modeling, and visualization. It is widely used as an alternative to R Markdown for exploratory and reproducible data analysis workflows. The other options do not provide the same integrated interactive coding and analysis environment.

2.

Explain how data science can be utilized in public health initiatives within the government sector.

  • To create advertisements for health products

  • To analyze health trends and allocate resources effectively

  • To monitor social media for public sentiment

  • To develop new medical technologies

Explanation

Explanation:

In the government sector, data science supports public health initiatives by analyzing large-scale health data to identify trends, track disease outbreaks, and allocate resources efficiently. By examining patient records, vaccination rates, and epidemiological data, policymakers can make informed decisions about health interventions, emergency responses, and resource distribution. While monitoring social media or developing medical technologies may be useful, the primary application in public health focuses on trend analysis and resource allocation.

Correct Answer:

To analyze health trends and allocate resources effectively


3.

A data analyst wants to perform an analysis and make it easy for colleagues to understand his process and update the analysis a year from now. Which tool is best to achieve this objective?

  • PDF document

  • Code chunks

  • R Markdown

  • Word Document

Explanation

Explanation:

R Markdown is the best tool for creating reproducible and dynamic reports. It allows analysts to combine narrative text, code chunks, and the resulting outputs (tables, plots, etc.) in a single document. This makes it easy for colleagues to follow the analysis workflow and update the report in the future, as the code can be re-run with new data without recreating the report from scratch. Unlike static PDFs or Word documents, R Markdown integrates code execution directly into the document.

Correct Answer:

R Markdown


4.

Why does an analyst use the JOIN command in Structured Query Language?

  • To update data in a database
  • To select a certain number of records
  • To combine rows and provide an output from two or more tables
  • To delete data from a database

Explanation

Explanation

Correct answer: (C.) To combine rows and provide an output from two or more tables
The JOIN clause in SQL is used to combine rows from two or more tables based on a related column between them. This allows analysts to retrieve and work with connected datasets in a single query output, enabling richer analysis across relational data structures. It does not modify data (UPDATE or DELETE) nor limit the number of records returned. Instead, its core purpose is integrating data from multiple tables into one result set.

5.

An analytics team uses a shared programming language to make dynamic files to save, organize, and document analysis using code chunks, comments, and other features. Which language is used for this purpose?

  • PHP
  • Java
  • Swift
  • R

Explanation

Explanation

Correct answer: (D.) R
The language used for creating dynamic, reproducible analysis files with code chunks, comments, and documentation features is R. It is widely used in data analytics and supports tools like R Markdown, which allows analysts to combine code execution, narrative text, and outputs in a single document. PHP is primarily used for web development, Java is a general-purpose programming language, and Swift is used mainly for Apple application development, so none of these provide the same integrated data analysis and reporting workflow as R.

6.

An analyst is working in two spreadsheets. One spreadsheet contains employee pay rates and identification numbers. The other spreadsheet contains the number of hours worked and the same employee identification numbers. How does the analyst search for the rate of pay from the pay-rates spreadsheet and add it to the employee-hours spreadsheet?

  • SUM
  • TRIM
  • VLOOKUP
  • VALUE

Explanation

Explanation

Correct answer: (C.) VLOOKUP
The analyst needs to retrieve matching information (pay rates) from one dataset using a shared identifier (employee ID) and bring it into another dataset. The VLOOKUP function is designed for this purpose because it searches for a value in the first column of a range and returns a corresponding value from another column in the same row. This makes it ideal for linking related data across separate spreadsheets. The other functions do not perform lookup-based data retrieval: SUM adds values, TRIM removes extra spaces from text, and VALUE converts text to numbers.

7.

A data analyst finds the code mdy(10211020) in an R script. What is the year of the date that is created?

  • 1021

  • 1020

  • 2120

  • 1102

Explanation

Explanation:

The mdy() function from the lubridate package in R interprets numbers or strings in month-day-year format. In the code mdy(10211020), the last four digits represent the year, which is 1020. The function converts the numeric input into a date object, correctly parsing the month and day from the first part and assigning the year from the last four digits.

Correct Answer:

1020


8.

When working in R, for which part of the data analysis process do analysts use the tidyr package?

  • Data visualization

  • Data calculations
     

  • Data security

  • Data cleaning

Explanation

Explanation:

The tidyr package in R is primarily used for data cleaning and tidying. It provides functions to reshape data, separate or unite columns, handle missing values, and convert datasets into a tidy format where each variable is a column and each observation is a row. This is a crucial step in the data analysis process because clean and well-structured data is necessary for accurate analysis and effective visualization.

Correct Answer:

Data cleaning


9.

A delimiter is a character that marks the beginning and end of _____.

  • a data item

  • an HTML report

  • a command line

  • an .rmd file

Explanation

Explanation:

A delimiter is a character or set of characters used to indicate the beginning and end of a data item. In data processing, delimiters are commonly used to separate values in a file, such as commas in CSV files or tabs in TSV files. This helps software correctly identify and parse individual pieces of data for analysis.

Correct Answer:

a data item


10.

How can businesses use Natural Language Processing (NLP) to improve customer experience?

  • By analyzing customer reviews and feedback to understand sentiment

  • By converting images into numerical data

  • By calculating transaction totals manually

  • By developing algorithms for data compression

Explanation

Explanation:

Natural Language Processing (NLP) allows businesses to automatically analyze customer feedback, reviews, and chat interactions to understand sentiment and satisfaction levels. By detecting positive, negative, or neutral emotions in textual data, companies can identify pain points and improve customer service strategies. This enables more personalized communication and data-driven decision-making to enhance overall customer experience.

Correct Answer:

By analyzing customer reviews and feedback to understand sentiment


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